grounding knowledge in the brain’s modal systems
DESCRIPTION
Grounding Knowledge in the Brain’s Modal Systems. Lawrence W. Barsalou Department of Psychology Emory University June 2010 Research supported by National Science Foundation grants SBR-9421326, SBR-9796200, SBR-9905024, BCS-0212134 DARPA grants FA8650-05-C-7256, FA8650-05-C-7255 - PowerPoint PPT PresentationTRANSCRIPT
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Grounding Knowledge in the Brain’s Modal Systems
Lawrence W. BarsalouDepartment of Psychology
Emory University
June 2010
Research supported by
National Science Foundation grantsSBR-9421326, SBR-9796200, SBR-9905024, BCS-0212134
DARPA grants FA8650-05-C-7256, FA8650-05-C-7255
Emory fMRI seed grants
Grounding Knowledge
Grounding Knowledge 2
The conceptual system
1. represents knowledge about experience in the world
2. organizes knowledge categorically• concepts in memory represent categories in the world
3. provides representational support across cognitive tasks• online processing
•high-level perception•categorization of perceived entities and events• inferences that go beyond the information given
• offline processing• in memory, language, and thought•conceptualization of entities not present
• guides learning•provides interpretations of novel material•expertise grows with conceptual vocabulary
Grounding Knowledge 3
The traditional approach: Semantic memorye.g., Tulving, 1972; Collins & Loftus, 1975
•modular• distinct from episodic memory and the brain’s modal systems (e.g., vision)
•amodal• non-perceptual representations
Grounding Knowledge 4
The transduction principle in amodal conceptual systems
•amodal symbols are transduced from modal states• constitute knowledge about categories
• a modular system with unique operating principles
soft
barks
legstail
pat
Grounding Knowledge 5
§¥ÞŧЭ
The transduction principle in amodal symbol systems
•amodal symbols are not linguistic symbols• the conceptual symbols that underlie language
• transduction underlies many common approaches to representation• feature lists, semantic nets, schemata, frames, production systems, etc.
Grounding Knowledge 6
“dog”
Representing knowledge in amodal symbol systems
•amodal symbols later represent categories in their absence• constitute the knowledge that underlies memory, language, thought
• no representations in modal systems required or involved
§¥ÞŧЭ
Grounding Knowledge 7
An alternative approach
•non-modular• concepts utilize sensory-motor and other modal systems (e.g., affect)
•modal• modal simulations represent concepts
Grounding Knowledge 8
Capturing neural activity in the brain’s modal systems Damasio (1989), Barsalou (1999, 2003, 2005), Simmons & Barsalou (2003)
•modal states are captured during online experience• by conjunctive neurons in hierarchically-organized association areas
•capture is partial• not complete
Grounding Knowledge 9
“dog”
Running simulations to represent knowledge
•simulations (reenactments) represent categorical knowledge• may often be unconscious, not necessarily conscious (as in imagery)
• always partial, may be distorted
• could be exemplars, averages of exemplars, etc.
Empirical evidence for simulation:A general computational mechanism in the brain
•evidence across disciplines• cognitive psychology• social psychology• developmental psychology• cognitive neuropsychology• cognitive neuroscience
•evidence across processes• perception (perceptual anticipation)• working memory (imagery and rehearsal)• implicit memory (sensory-motor priming)• explicit memory (recollection)• knowledge representation (conceptualization)• language (meaning)• thought (envisioning possible scenarios)• social cognition (mirroring and empathy)
Grounding Knowledge 10
For a recent review see:Barsalou, L.W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617-645.
Conjecture:Multiple control systems.
One representation system.
Grounding Knowledge 11
Common misperceptions
•NOT a classic empiricist theory• in principle, simulations for categories could be genetically determined
• strong genetic constraints determine feature systems and association areas
•anticipating important categories in evolutionary history
•NOT a recording system, symbolic operations are central (Pylyshyn, 1973)
• doesn’t simply capture records of experience
• instead, interpretation of experience lies at the core of this account
•via symbolic operations
•implemented with mechanisms not presented today
•knowledge does NOT solely reflect perception of the external world• also perception of mental states, meta-cognition, affect, etc. (“introspection”)
• central to abstract concepts
Grounding Knowledge 12
Overview of research to be presented
1. Examples of simulation
2. Simulation in situated action
3. Simulation in natural abstract categories
4. Simulation in symbolic operations• predication
• conceptual combination
12Grounding Knowledge
Grounding Knowledge 13
Overview of research to be presented
1. Examples of simulation
2. Simulation in situated action
3. Simulation in natural abstract categories
4. Simulation in symbolic operations• predication
• conceptual combination
13Grounding Knowledge
Grounding Knowledge 14
Shape inferences in comprehensionZwaan, Stanfield, and Yaxley (2002)
•hypothesis• if readers simulate the meaning of a text to understand it, then text representations should have perceptual properties, even when these properties are not mentioned
•method• a sentence was presented
• a picture was presented and participants had to name it as quickly as possible
•key manipulation• whether or not the pictured object had a shape that matched the shape of the object implied in the sentence
The bird sat quietly in the tree (implies a bird with its wings folded)
The bird flew quickly across the sky (implies a bird with its wings flapping)
Examples of sentences Examples of pictures
Mentioned Not Mentioned
Grounding Knowledge 15
Results
•conclusion• when comprehending sentences, participants simulated the scenes described,thereby committing to a particular shape of the objects mentioned
Nam
ing
RT
(m
s)
Picture Shape
Grounding Knowledge 16
Simulating actions to represent verb meaningHauk, Johnsrude, and Pulvermüller (2004)
•method• participants read isolated words in an fMRI scanner (2.5 sec rate)
• subsets of words referred to face, arm, or leg movements (mixed with non-motor words)
•e.g., “lick,” “pick,” “kick”
• participants later performed actual motor movements (localizer task)
•i.e., moved their tongue, finger, or foot
•prediction• if simulations represent word meanings,then words for different body part movementsshould activate the respective regions of the motor system
• these activations should also lie near thosefor the localizer task
Grounding Knowledge 17
Results
• the predicted somatotopic order of word activations appeared• activations occurred in the motor system for the action words
•relative to reading strings of hash marks
• leg activations were vertically highest, then arm, then face
• leg and arm activations overlapped for the word and localizer tasks
• face discrepancies could indicate less correspondence between words and the localizer task
Grounding Knowledge 18
Overview of research to be presented
1. Examples of simulation
2. Simulation in situated action
3. Simulation in natural abstract categories
4. Simulation in symbolic operations• predication
• conceptual combination
18Grounding Knowledge
Grounding Knowledge 19
Conceptual processing is situatedBarsalou (2003), Smith & Semin (2004), Yeh & Barsalou (2006)
•situations frame conceptual representations• concepts are not learned and represented in a vacuum
• concepts are learned and represented in a situated manner
•background situations prepare agents for situated action• provide useful inferences about:
•settings
•agents and objects
•actions and events
•mental states
• tailored to different courses of situated action for the same concept
•e.g., chairs in living rooms vs. offices vs. jets
•situational inferences delivered via multimodal simulations• across the relevant modalities
Grounding Knowledge 20
Situating physical objects Wu and Barsalou (2009)
• task and results• participants produced the features of objects (e.g., apple)
• produced non-requested information about settings and mental states
• suggests that they situated their conceptualizations of the objects
Grounding Knowledge 21
Situating manipulable objects Chao & Martin (2000)
•participants viewed manipulable objects• activation occurred in motor and parietal areas associated with manipulating objects (but did not occur for non-graspable objects)
•participants situated the manipulable objects with respect to action• on categorizing a visual picture, motor inferences were produced
•review of related findings• Lewis (2006)
Taste inferences for foodsSimmons, Martin, & Barsalou (2005)
•presented participants with pictures of foods and houses• relatively tasty foods from the undergraduate perspective
•no fruits and vegetables
• 1-back task
• food pictures should activate categorically-related inferences
• taste areas should become active
Situated Simulation 22
Situated Simulation 23
64, -4, 20 tasting sucrose - deAraujo et al. (2003), p.2063 - R. Operculum 36, 0, 16 tasting chocolate - Small et al. (2001), p.1724 - R Insula/Operculum54, 12, 10 tasting umami - deAraujo et al. (2003), p.316 - R Insula/Operculum45, 3, 5 tasting glucose - Francis et al. (1999), p.457 - operculum45, 1, -9 tasting sucrose - deAraujo et al. (2003), p.2063 – Anterior Insula36, -6, 9 viewing food pictures - Simmons, Martin, & Barsalou- R Insula/operculum
Activations in primary gustatory cortex for foods(frontal operculum)
Z = 20 Z = 16 Z = 10 Z = 9 Z = 5 Z = -9
Situated Simulation 24
Z = -30
Z = -24
Z = -20
Z = -18
Z = -10
Z = -6
-4, 51, -30 abstract reward - O'Doherty ,et al. (2001)-10 ,42, -24 abstract reward - O'Doherty ,et al. (2001)-4, 30, -20 abstract reward - O'Doherty ,et al. (2001)-9, 26, -18 tasting glucose - Frances, Rolls, et.al. (1999)-32, 50, -10 flavor center - de Araujo et, Rolls, Kingelbach, et al. (2003)-18, 48, -10 property verification, - Simmons, Pecher, Hamann, et al. (submitted)-34, 26, -6 tasting umami- de Aaujo, et al. (2003)-21, 33, -18 viewing food pictures- Simmons, Martin, & Barsalou
Activations in the taste reward area for foods(orbitofrontal cortex)
Grounding Knowledge 25
Situating social objectsGil-da-Costa, Braun, Lopes, Hauser, Carson, Herscovitch, & Martin (2004)
•monkeys listened to recorded coos and screams of other monkeys• compared PET activations to those for unfamiliar sounds (musical instruments)
•results• activations in auditory areas (perception)• activations for situated inferences
•visual areas• inferior temporal (faces)• superior temporal (expression, motion)
•frontal and limbic areas• medial prefrontal (mental states?)• amgydala (emotion)• hippocampus (emotional memory)
• the monkeys simulated the situations associated with the sounds• provides continuity with the human conceptual system (Barsalou, 2005)
A
D EC
BA
D EC
B
Grounding Knowledge 26
Overview of research to be presented
1. Examples of simulation
2. Simulation in situated action
3. Simulation in natural abstract categories
4. Simulation in symbolic operations• predication
• conceptual combination
26Grounding Knowledge
Representing abstract concepts with simulationBarsalou (1999)
•concepts are typically situated• not represented in vacuum, but in a setting with agents, objects, events, etc.
•concrete concepts• objects, settings, and actions in situations• relatively “local” in time and space• perceived externally
•abstract concepts• complex configurations of information distributed across settings and events• internally perceived content especially important
• e.g., mental states, affect, cognitive operations
•simulating abstract concepts • simulating the associated configuration of information,including mental states and events
27Grounding Knowledge
Schwanenflugel (1991)
28
Exploratory study Barsalou & Wiemer-Hastings (2005)
•method• participants produced properties for abstract and concrete concepts
• TRUTH, FREEDOM, INVENTION vs. SOFA, BIRD, CAR
•results• participants produced broad situational content for both types of concepts
•people generally situate both kinds of concepts
• abstract concepts activated more mental state and setting/event properties, whereas concrete concepts activated more entity properties
•the two kinds of concepts rely on different situational information
Proportions of property types
Concept type Entity Setting/Event Mental State Concrete .26 .46 .21 Abstract .15 .52 .28
28Grounding Knowledge
29
Assessing simulation in abstract concepts with fMRIWilson, Simmons, Martin, & Barsalou (in preparation)
• two phases of the experiment
• localizer phase• identified brain areas that perform abstract forms of processing
• blocked design
•priming phase• assessed the semantic content of two abstract concepts
• fast event-related design
•hypothesis• simulations of abstract processing will represent the abstract concepts
LocalizerPhase
Semantic PrimingPhase
29Grounding Knowledge
30
• thoughts localizer• participants viewed blocks of complex scenes
• for each picture, participants answered the following question to themselves
•“What are the thoughts of people in the picture?”
•counting localizer• participants viewed blocks of complex scenes
• for each picture, participants answered the following question to themselves
•“How many entities are there in the picture?”
LocalizerPhase
Semantic PrimingPhase
Note. Localizer blocks were also included for two concrete localizers, color and motion, not discussed here.
30Grounding Knowledge
31
LocalizerPhase
Semantic PrimingPhase
• thoughts – counting• medial prefrontal, precuneus
• bilateral anterior and superior temporal
•counting – thoughts• bilateral intraparietal sulcus
p < .0001, corrected, random effects31Grounding Knowledge
L
R
x = -45
x = 48
x = -5
y = -60L
32
•semantic priming trials• fast-event related design
•concepts ordered randomly
•random ISI jitter
•catch trials to deconvolveword primes and pictures
• possible responses: “Word applies” or “Word doesn’t apply”
• pictures promoted deepsemantic processing
•hypothesis• simulations underlie meaning
LocalizerPhase
Semantic PrimingPhase
convince
5 sec(fMRI images of interest)
Response
2.5 sec
Note. Semantic priming trials were also included for two concrete concepts red and rolling, not discussed here.
arithmetic
5 sec(fMRI images of interest)
Response
2.5 sec
32Grounding Knowledge
33
•convince – arithmetic• dark blue areas
• medial prefrontal, precuneus, superior temporal
• no arithmetic – convince activations in localizer areas
• simulations underlie meaning
•arithmetic – convince• orange areas
• intraparietal sulcus
• no convince – arithmeticactivations in localizer areas
• simulations underlie meaning
LocalizerPhase
Semantic PrimingPhase
p < .05, corrected, random effects33Grounding Knowledge
L y = -45
A
L
R
x = -45
x = 48
x = -5
y = -60L
3434Grounded Cognition
Assessing simulation in abstract concepts with fMRIWilson, Barrett, Simmons, Barsalou (in preparation)
Physical Threat Situation You row on a lake to experience the feel of storm waves. As you head toward the middle of the lake, white-capped waves break across your small boat with increasing frequency. As the waves become increasingly rough, water pours into the boat. The boat sinks. You try to keep your head above water, as wave after wave crashes over you. Your wet clothes feel heavy on your body, making it difficult to stay afloat.
Social Threat SituationYou’re leading an important group presentation at work. You’re unprepared for your boss’s questions because a couple of co-workers didn’t pull their weight in preparing for the meeting. The presentation finishes awkwardly. Your boss thanks you coolly. His associates sit looking at each other, wondering what to say next. You can feel the sweat forming under your arms.
OBSERVE
TASK“How easy was it for you to experience
OBSERVE in the context of the situation?”
Very easy (3), Somewhat easy (2), Not easy (1)
Other concepts used: PLAN FEAR ANGER
Grounded Cognition 35
BOLD responses only to words,p < .05, corrected, random effects
Visual processing(bilateral superior occipital)
Auditory processing(bilateral superior temporal)
Object processing(bilateral fusiform, BA 37)
Observe – (Fear, Anger)physical situationssocial situationsboth
x = -32 x = 55x = -47
R R Rz = 26 z = 5z = -8
OBSERVE activations as a function of situation
Physical Social Overlap
1. L. Sup. Temporal extends into pole, insula
2. R. Sup. Temporal extends into pole
3.Bilateral Mid Occipital extends into inf. parietal
4. L. ITG/MTG extends into fusiform, PHC
6. R. ITG/MTG
7. Precuneus
8. Mid Cingulate
9. R. Middle Frontal
10. R. Insula
z = -12
z = 28
y = -17
8% 83% 9%
Grounded Cognition
BOLD responses only to words,p < .05, corrected, random effects
Grounding Knowledge 37
Overview of research to be presented
1. Examples of simulation
2. Simulation in situated action
3. Simulation in natural abstract categories
4. Simulation in symbolic operations• predication
• conceptual combination
37Grounding Knowledge
Grounding Knowledge 38
Symbolic operations
• typically viewed as a problem for grounded views• assumed to be possible only in amodal symbolic systems
• examples of symbolic operations• predication “Pumpkins are orange” ORANGE (pumpkins)
• conceptual combination “The cat is on the sofa” ON (cat, sofa)
• simulation-based accounts of symbolic operationsBarsalou, L.W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22,
577-609.
Barsalou, L.W. (2003). Abstraction in perceptual symbol systems. Philosophical Transactions of the Royal Society of London: Biological Sciences, 358, 1177-1187.
Barsalou, L.W. (2008). Grounding symbolic operations in the brain’s modal systems. In G.R. Semin & E.R. Smith (Eds.), Embodied grounding: Social, cognitive, affective, and neuroscientific approaches (pp. 9-42). New York: Cambridge University Press.
Grounding Knowledge 39
Overview of research to be presented
1. Examples of simulation
2. Simulation in situated action
3. Simulation in natural abstract categories
4. Simulation in symbolic operations• predication
• conceptual combination
39Grounding Knowledge
Grounding Knowledge 40
Grounding color semantics in the visual systemSimmons, Ramjee, Beauchamp, McRae, Martin, & Barsalou (2007)
•participants verified “possible” properties of conceptsin an fMRI scanner
• color properties
• motor properties
•hypothesis• verifying color properties produces color simulations in the brain’s color perception system
•builds on previous findings in the literature• e.g., Chao & Martin (1999), Oliver & Thompson-Schill (2003)
MILK..
white..
(true)
WATER..
white..
(false)
DOOR KNOB..
turned..
(true)
•10 participants, event-related design (168 trials across 7 runs)• concept-only catch trials used to deconvolve concepts and properties
Grounding Knowledge 41
Color localizer task Establishing the color perception areas
• the Farnsworth-Munsell color judgment task (adapted for fMRI)• participants judged whether or not hues are ordered from lightest to darkest
• for multiple chromatic and achromatic wheels
• performed after the property verification scanning runs
Chromatic Achromatic
Ordered
Not ordered• blocked design, 4 runs• 3 chromatic blocks / run• 3 achromatic blocks / run
LocalizerProperty
Verification
Grounding Knowledge 42
Chromatic > Achromatic Wheels
Areas active for color perception
p < .05, corrected, random effects
Left
Front
LocalizerProperty
Verification
Grounding Knowledge 43
Color > Motor Properties
Areas active for verifying color properties
p < .05, corrected, random effectsLeft
Front
LocalizerProperty
Verification
Grounding Knowledge 44
Overlap
Chromatic > Achromatic Wheels
Color > Motor Properties
Overlapping activations for verifying color properties and
perceiving color
A subsequent ROI analysis on the fusiform cluster identified by the color perception task (-33, -36, -9) found color > motor properties, p < .05, corrected, random effects.
Tootell et al. (2004) argue that this overlapping area is a primary color processing area in macaques
Left
Front
Grounding Knowledge 45
Overview of research to be presented
1. Examples of simulation
2. Simulation in situated action
3. Simulation in natural abstract categories
4. Simulation in symbolic operations• predication
• conceptual combination
45Grounding Knowledge
46
Occlusion effects in conceptual combinationWu & Barsalou (2009)
• in perception, occluded features are less salient than unoccluded ones• for LAWN, dirt and roots are less salient than green and blades
• in conceptual processing, is there an analogous occlusion effect?• if simulation is used to combine meanings, there should be
•nouns task• some participants generated features for nouns having occluded features
•neutral instructions (nothing mentioned about imagery)• simulation prediction:
• unoccluded features should be produced more than occluded featuresLAWN green, blades > dirt, roots
•noun phrases (NPs) task• other participants generated features for NPs with revealing modifiers
•either novel or familiar NPs (neutral instructions)• simulation prediction:
•occluded features should be produced more often than for isolated nounsROLLED-UP LAWN dirt, roots > LAWN dirt, roots
46Grounding Knowledge
47
Results
•occlusion affected conceptual processing• external features more likely than internal features for nouns• internal features become more likely for both novel and familiar NPs
47Grounding Knowledge
• not the result of rules associated with modifiers• e.g., occluded features are not produced more often for ROLLED UP SNAKE than for SNAKE
Grounding Knowledge 48
Assessing conceptual combination with fMRIJames, Simmons, Barbey, Hu, & Barsalou (in preparation)
• two critical kind of trials• independent " . . "
• combination " − . "
• fast event-related design• trial types interspersed randomly
• random ISI jitter
• catch trials to deconvolvemodifiers and head nouns
• familiarity responses at " . "• “Occurs once a month or more” or
• “Occurs less than once a month”
distressed . reverend .
Modifier1 sec
Head Noun1 sec
3 sec
FamiliarityJudge Modifier
FamiliarityJudge Head Noun
3 sec
distressed − reverend .
Modifier1 sec
Head Noun1 sec
3 sec
FamiliarityJudge Noun Phrase
3 sec
Independent Trials
Combination Trials
Grounding Knowledge 49
Examples of modifiers and head nouns
•mental state modifiersdistressed reverend
pleasing cloves
•motion modifierssoaring balloon
swaying oak
• location modifiersocean shrimp
auditorium piano
• no modifier or head noun repeated
• head nouns counter-balanced forlength, frequency, category, typicality
• words counter-balanced across participants so that every word occurred in both the independent and combination conditions
distressed . reverend .
Modifier1 sec
Head Noun1 sec
3 sec
FamiliarityJudge Modifier
FamiliarityJudge Head Noun
3 sec
distressed − reverend .
Modifier1 sec
Head Noun1 sec
3 sec
FamiliarityJudge Noun Phrase
3 sec
Independent Trials
Combination Trials
Mental State modifiers – Motion and Location Modifiers
Motion modifiers – Mental State and Location Modifiers
Location modifiers – Mental State and Motion Modifiers
Grounding Knowledge 50
Grounding Knowledge 51
Simulations in modal areas represented the modifiers
• areas more active for one modifier modality than for the other two, p < .05, corrected, random effects
IndependentMental State Modifiers
(distressed, pleasing)
IndependentLocation Modifiers(e.g., ocean, auditorium)
IndependentMotion Modifiers
(soaring, swaying)
medial pre-frontal(mental states area)
L temporal(motion area)
LR parahippocampus(location area)
L L
L
L
x=-9 y=-54
z=-11
y=-33
z=17 z=-3
L
Mental State modifiers – Motion and Location Modifiers
Motion modifiers – Mental State and Location Modifiers
Location modifiers – Mental State and Motion Modifiers
Grounding Knowledge 52
Grounding Knowledge 53
Mental State Modifiers(distressed, pleasing)
Location Modifiers(e.g., ocean, auditorium)
Motion Modifiers(soaring, swaying)
Combined Modifiers
Independent Modifiers
Combined Modifiers (All) – Independent Modifiers (All)
Grounding Knowledge 54
Grounding Knowledge 55
Combined modifiers − Independent modifiers
•conjecture• the conceptual system holds off committing to a specific sense of the modifier
• a right hemisphere network infers a situation that contains the modifier and a predicted head noun
• areas more active for combined modifiers across modalities than for independent modifiers across modalities, p < .05, corrected, random effects• the same areas were generally active for individual modalities, but less robustly
R inferior parietalR supramarginalR superior temporal
y=-51 y=44 z=28L L
R medial frontal
z=43 x=40L x=27
Combined Nouns (All) – Independent Nouns (All)
Grounding Knowledge 56
• areas more active for combined nouns across modalities than for independent nouns across modalities, p < .05, corrected, random effects• similar areas were generally active for individual modalities, but less robustly
Grounding Knowledge 57
Combined nouns – Independent nouns
•conjecture• this bilateral multimodal network simulates a specific situation in which the modifier and head noun concepts have been integrated
LR parahipp gyrusLR fusiform gyrusLR lingual gyrus
L superior temporalLR precuneusL inferior frontal
L
L pre-central gyrusLR post central gyrusLR inferior parietal
L L L
L Ly=-53
z=45 z=18
x=-14
z=2
y=-38
Grounding Knowledge 58
Conclusions
•simulation underlies a wide variety of conceptual processes• representation of object categories
• representation of abstract categories
• symbolic operations (predication, conceptual combination)
•simulations of concepts are situated• represent background information about situations relevant to goal pursuit
58Grounding Knowledge
Grounding Knowledge 59
Contributors
• post docs• Anna Borghi• Andy James• Diane Pecher• Rene Zeelenberg
• graduate students• Aron Barbey• Sergio Chaigneau• Linda Confalonieri• Shlomit Finkelstein• Carla Harenski• Irene Kan• Zhaohui Liu• Barbara Luka• Jesse Prinz• Daniel Richardson• Ava Santos• Kyle Simmons• Karen Solomon• Saskia van Dantzig• Christy Wilson• Ling-Ling Wu• Wenchi Yeh
• undergraduates• Melissa Armstrong• Joy Lynn Brasfield• Shurin Hase• Vimal Ramjee• Christy Wilson
• faculty• Lisa Barrett• Michael Beauchamp• Cynthia Breazeal• Andy Butler• Zach Estes• Rob Goldstone• Stephan Hamann• Xiaoping Hu• Alex Martin• Ken McRae• Paula Niedenthal• Giuseppe Pagnoni• Linda Smith• Michael Spivey• Sharon Thompson-Schill• Katja Wiemer-Hastings• Phil Wolff